Overview

Dataset statistics

Number of variables50
Number of observations48982
Missing cells388519
Missing cells (%)15.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.7 MiB
Average record size in memory400.0 B

Variable types

CAT32
NUM18

Warnings

FECHAENTRADA has a high cardinality: 494 distinct values High cardinality
FECHASALIDA has a high cardinality: 426 distinct values High cardinality
FECHAACTUALIZACION has a high cardinality: 395 distinct values High cardinality
FECHAMORADESDE has a high cardinality: 1921 distinct values High cardinality
FECHAMOVIMIENTO has a high cardinality: 517 distinct values High cardinality
VCTO_CUOTA1 has a high cardinality: 954 distinct values High cardinality
FECHA_VCTO has a high cardinality: 2047 distinct values High cardinality
FECHAULTPAGO has a high cardinality: 1130 distinct values High cardinality
MUNICRESIDENCIA has a high cardinality: 824 distinct values High cardinality
IES has a high cardinality: 297 distinct values High cardinality
NOMBREPROGRAMA has a high cardinality: 2279 distinct values High cardinality
SUBLINEA has a high cardinality: 74 distinct values High cardinality
FECHA_ACUERDO has a high cardinality: 1423 distinct values High cardinality
fecha Venc Cuota Vigente has a high cardinality: 103 distinct values High cardinality
Valor Cuota Vigente has a high cardinality: 6843 distinct values High cardinality
RazonSocial has a high cardinality: 19241 distinct values High cardinality
UltimoPeriodoCotizado has a high cardinality: 174 distinct values High cardinality
Tipificacion has a high cardinality: 92 distinct values High cardinality
SALDOCAPITALACIERRE is highly correlated with SALDOTOTAL_ACT and 1 other fieldsHigh correlation
SALDOTOTAL_ACT is highly correlated with SALDOCAPITALACIERRE and 1 other fieldsHigh correlation
CAPITALICETEX_ACT is highly correlated with SALDOTOTAL_ACT and 1 other fieldsHigh correlation
SUBLINEA is highly correlated with LINEAHigh correlation
LINEA is highly correlated with SUBLINEAHigh correlation
FECHASALIDA has 37376 (76.3%) missing values Missing
FECHAMORADESDE has 6955 (14.2%) missing values Missing
NROCUOTASMORA has 651 (1.3%) missing values Missing
CALIFICACIONACTUAL has 2592 (5.3%) missing values Missing
VCTO_CUOTA1 has 1034 (2.1%) missing values Missing
FECHA_VCTO has 990 (2.0%) missing values Missing
FECHAULTPAGO has 28842 (58.9%) missing values Missing
IES has 1136 (2.3%) missing values Missing
NOMBREPROGRAMA has 1148 (2.3%) missing values Missing
ESTADOACTUAL has 2909 (5.9%) missing values Missing
ESTRATO has 3002 (6.1%) missing values Missing
SEXO has 3123 (6.4%) missing values Missing
ESTADOCIVIL has 2964 (6.1%) missing values Missing
Rangodiasmora has 12305 (25.1%) missing values Missing
CONCEPTO has 14625 (29.9%) missing values Missing
FECHA_ACUERDO has 15306 (31.2%) missing values Missing
ESTADO_ACUERDO has 15306 (31.2%) missing values Missing
TIPO_ACUERDO has 15306 (31.2%) missing values Missing
CUOTAS_PAGADAS_ACUERDO has 23473 (47.9%) missing values Missing
CUOTAS_MORA_ACUERDO has 23473 (47.9%) missing values Missing
CUOTAS_FUTURAS_ACUERDO has 23473 (47.9%) missing values Missing
fecha Venc Cuota Vigente has 33410 (68.2%) missing values Missing
Valor Cuota Vigente has 15306 (31.2%) missing values Missing
No. ACUERDOS DE PAGO has 15306 (31.2%) missing values Missing
RazonSocial has 17908 (36.6%) missing values Missing
UltimoPeriodoCotizado has 14172 (28.9%) missing values Missing
FechaFosyga has 14172 (28.9%) missing values Missing
Hora_ContactoEfectivo has 20802 (42.5%) missing values Missing
Llamadas_recibidas has 11236 (22.9%) missing values Missing
Llamadas_realizadas has 3240 (6.6%) missing values Missing
Tipificacion has 2524 (5.2%) missing values Missing
VALORCUOTA is highly skewed (γ1 = 33.51314313) Skewed
CUOTAS_FUTURAS_ACUERDO is highly skewed (γ1 = 21.17064286) Skewed
IDSOLICITUD has unique values Unique
NROCUOTASMORA has 5602 (11.4%) zeros Zeros
NUMDIASMORA_ACT has 8733 (17.8%) zeros Zeros
VALORCUOTA has 786 (1.6%) zeros Zeros
SALDOTOTALMORA1_ACT has 8418 (17.2%) zeros Zeros
SALDOTOTAL_ACT has 2105 (4.3%) zeros Zeros
CODSNIES_INST has 828 (1.7%) zeros Zeros
CAPITALICETEX_ACT has 3863 (7.9%) zeros Zeros
CUOTAS_PAGADAS_ACUERDO has 14348 (29.3%) zeros Zeros
CUOTAS_MORA_ACUERDO has 12558 (25.6%) zeros Zeros
CUOTAS_FUTURAS_ACUERDO has 25087 (51.2%) zeros Zeros

Reproduction

Analysis started2020-12-01 20:03:18.791605
Analysis finished2020-12-01 20:04:47.377204
Duration1 minute and 28.59 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

IDSOLICITUD
Real number (ℝ≥0)

UNIQUE

Distinct48982
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1511724.602
Minimum23
Maximum3934204
Zeros0
Zeros (%)0.0%
Memory size382.7 KiB
2020-12-01T15:04:47.485135image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile79240.8
Q1432336
median1609889
Q32309858.25
95-th percentile3091331.55
Maximum3934204
Range3934181
Interquartile range (IQR)1877522.25

Descriptive statistics

Standard deviation987382.5691
Coefficient of variation (CV)0.6531497655
Kurtosis-1.103970038
Mean1511724.602
Median Absolute Deviation (MAD)914245.5
Skewness0.04443426226
Sum7.404729444e+10
Variance9.749243378e+11
MonotocityNot monotonic
2020-12-01T15:04:47.654115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
34754551< 0.1%
 
29771591< 0.1%
 
17012681< 0.1%
 
30672831< 0.1%
 
15464471< 0.1%
 
4124131< 0.1%
 
2738071< 0.1%
 
17852291< 0.1%
 
690031< 0.1%
 
26290011< 0.1%
 
Other values (48972)48972> 99.9%
 
ValueCountFrequency (%) 
231< 0.1%
 
391< 0.1%
 
471< 0.1%
 
601< 0.1%
 
681< 0.1%
 
ValueCountFrequency (%) 
39342041< 0.1%
 
38973161< 0.1%
 
38633491< 0.1%
 
38285301< 0.1%
 
38283151< 0.1%
 

FECHAENTRADA
Categorical

HIGH CARDINALITY

Distinct494
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size382.7 KiB
2019-11-13
16752 
2020-07-07
10140 
2020-09-08
1873 
2020-09-22
 
1534
2020-06-24
 
1508
Other values (489)
17175 
ValueCountFrequency (%) 
2019-11-131675234.2%
 
2020-07-071014020.7%
 
2020-09-0818733.8%
 
2020-09-2215343.1%
 
2020-06-2415083.1%
 
2018-11-0112132.5%
 
2020-08-1811152.3%
 
2020-02-2610932.2%
 
2020-11-107861.6%
 
2020-11-017181.5%
 
Other values (484)1225025.0%
 
2020-12-01T15:04:47.872193image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique133 ?
Unique (%)0.3%
2020-12-01T15:04:48.036191image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

FECHASALIDA
Categorical

HIGH CARDINALITY
MISSING

Distinct426
Distinct (%)3.7%
Missing37376
Missing (%)76.3%
Memory size382.7 KiB
2020-08-19
1035 
2019-04-04
 
300
2020-11-10
 
228
2020-10-16
 
214
2019-11-12
 
160
Other values (421)
9669 
ValueCountFrequency (%) 
2020-08-1910352.1%
 
2019-04-043000.6%
 
2020-11-102280.5%
 
2020-10-162140.4%
 
2019-11-121600.3%
 
2020-09-231390.3%
 
2019-01-151310.3%
 
2020-10-081290.3%
 
2019-05-071170.2%
 
2020-11-111170.2%
 
Other values (416)903618.4%
 
(Missing)3737676.3%
 
2020-12-01T15:04:48.200028image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique33 ?
Unique (%)0.3%
2020-12-01T15:04:48.375180image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length3
Mean length4.658609285
Min length3

FECHAACTUALIZACION
Categorical

HIGH CARDINALITY

Distinct395
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size382.7 KiB
2019-11-13
14471 
2020-07-07
9633 
2020-09-08
 
1863
2020-09-22
 
1538
2020-06-24
 
1460
Other values (390)
20017 
ValueCountFrequency (%) 
2019-11-131447129.5%
 
2020-07-07963319.7%
 
2020-09-0818633.8%
 
2020-09-2215383.1%
 
2020-06-2414603.0%
 
2020-02-2611112.3%
 
2020-08-1910472.1%
 
2020-11-108941.8%
 
2020-07-036591.3%
 
2019-04-043110.6%
 
Other values (385)1599532.7%
 
2020-12-01T15:04:49.008126image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique5 ?
Unique (%)< 0.1%
2020-12-01T15:04:49.183204image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

FECHAMORADESDE
Categorical

HIGH CARDINALITY
MISSING

Distinct1921
Distinct (%)4.6%
Missing6955
Missing (%)14.2%
Memory size382.7 KiB
2019-01-05
 
2595
2017-07-05
 
1111
2019-05-05
 
953
2018-11-05
 
876
2019-02-05
 
870
Other values (1916)
35622 
ValueCountFrequency (%) 
2019-01-0525955.3%
 
2017-07-0511112.3%
 
2019-05-059531.9%
 
2018-11-058761.8%
 
2019-02-058701.8%
 
2018-02-058131.7%
 
2017-01-207441.5%
 
2019-04-056581.3%
 
2019-03-205471.1%
 
2018-08-055341.1%
 
Other values (1911)3232666.0%
 
(Missing)695514.2%
 
2020-12-01T15:04:49.352223image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique752 ?
Unique (%)1.8%
2020-12-01T15:04:49.534233image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.006063452
Min length3

NROCUOTASMORA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct91
Distinct (%)0.2%
Missing651
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean14.73381474
Minimum0
Maximum124
Zeros5602
Zeros (%)11.4%
Memory size382.7 KiB
2020-12-01T15:04:49.695308image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median13
Q321
95-th percentile47
Maximum124
Range124
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.54075128
Coefficient of variation (CV)0.9868965734
Kurtosis1.085486307
Mean14.73381474
Median Absolute Deviation (MAD)11
Skewness1.139595524
Sum712100
Variance211.4334477
MonotocityNot monotonic
2020-12-01T15:04:49.873193image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1878917.9%
 
0560211.4%
 
1730016.1%
 
1224244.9%
 
5516033.3%
 
2415403.1%
 
1414422.9%
 
2014042.9%
 
1613932.8%
 
1813612.8%
 
Other values (81)1977240.4%
 
ValueCountFrequency (%) 
0560211.4%
 
1878917.9%
 
210872.2%
 
38251.7%
 
47991.6%
 
ValueCountFrequency (%) 
1241< 0.1%
 
1181< 0.1%
 
1101< 0.1%
 
1081< 0.1%
 
1071< 0.1%
 

NUMDIASMORA_ACT
Real number (ℝ≥0)

ZEROS

Distinct2791
Distinct (%)5.7%
Missing74
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean699.8280445
Minimum0
Maximum7105
Zeros8733
Zeros (%)17.8%
Memory size382.7 KiB
2020-12-01T15:04:50.051232image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median548
Q31003
95-th percentile2428
Maximum7105
Range7105
Interquartile range (IQR)998

Descriptive statistics

Standard deviation808.4130065
Coefficient of variation (CV)1.155159489
Kurtosis4.28414568
Mean699.8280445
Median Absolute Deviation (MAD)522
Skewness1.890921665
Sum34227190
Variance653531.5891
MonotocityNot monotonic
2020-12-01T15:04:50.216112image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0873317.8%
 
428475.8%
 
54822814.7%
 
4287631.6%
 
57141.5%
 
5177061.4%
 
66601.3%
 
10276391.3%
 
6456311.3%
 
6095521.1%
 
Other values (2781)3038262.0%
 
ValueCountFrequency (%) 
0873317.8%
 
1450.1%
 
2380.1%
 
3320.1%
 
428475.8%
 
ValueCountFrequency (%) 
71051< 0.1%
 
57962< 0.1%
 
57651< 0.1%
 
55831< 0.1%
 
54671< 0.1%
 

VALORCUOTA
Real number (ℝ)

SKEWED
ZEROS

Distinct46532
Distinct (%)95.6%
Missing319
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean229429.5811
Minimum-222527.42
Maximum38757829
Zeros786
Zeros (%)1.6%
Memory size382.7 KiB
2020-12-01T15:04:50.418182image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-222527.42
5-th percentile23082.654
Q195207.5
median164259.85
Q3268769.5
95-th percentile583414.8
Maximum38757829
Range38980356.42
Interquartile range (IQR)173562

Descriptive statistics

Standard deviation456157.3658
Coefficient of variation (CV)1.988223853
Kurtosis1881.28009
Mean229429.5811
Median Absolute Deviation (MAD)81033.4
Skewness33.51314313
Sum1.116473171e+10
Variance2.080795424e+11
MonotocityNot monotonic
2020-12-01T15:04:50.580201image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
07861.6%
 
8254317< 0.1%
 
88010< 0.1%
 
878818< 0.1%
 
828178< 0.1%
 
1150378< 0.1%
 
549728< 0.1%
 
1058078< 0.1%
 
1008957< 0.1%
 
1137637< 0.1%
 
Other values (46522)4779697.6%
 
(Missing)3190.7%
 
ValueCountFrequency (%) 
-222527.421< 0.1%
 
-68484.11< 0.1%
 
-3160.871< 0.1%
 
07861.6%
 
0.111< 0.1%
 
ValueCountFrequency (%) 
387578291< 0.1%
 
267951641< 0.1%
 
245086151< 0.1%
 
22408113.991< 0.1%
 
184461181< 0.1%
 

SALDOTOTALMORA1_ACT
Real number (ℝ≥0)

ZEROS

Distinct39887
Distinct (%)82.0%
Missing319
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean4326886.624
Minimum0
Maximum95345584.28
Zeros8418
Zeros (%)17.2%
Memory size382.7 KiB
2020-12-01T15:04:50.805248image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1199752.28
median2409915.18
Q35676536.385
95-th percentile15463038.59
Maximum95345584.28
Range95345584.28
Interquartile range (IQR)5476784.105

Descriptive statistics

Standard deviation6327928.17
Coefficient of variation (CV)1.462466831
Kurtosis20.96088343
Mean4326886.624
Median Absolute Deviation (MAD)2359520.66
Skewness3.605394993
Sum2.105592838e+11
Variance4.004267493e+13
MonotocityNot monotonic
2020-12-01T15:04:50.985159image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0841817.2%
 
1604594.1717< 0.1%
 
4460496.487< 0.1%
 
5385244.597< 0.1%
 
1966423.687< 0.1%
 
1406082.316< 0.1%
 
2073324.436< 0.1%
 
1638433.446< 0.1%
 
3090958.65< 0.1%
 
1338213.815< 0.1%
 
Other values (39877)4017982.0%
 
(Missing)3190.7%
 
ValueCountFrequency (%) 
0841817.2%
 
1.011< 0.1%
 
1.041< 0.1%
 
1.11< 0.1%
 
1.111< 0.1%
 
ValueCountFrequency (%) 
95345584.281< 0.1%
 
89503374.451< 0.1%
 
83325425.361< 0.1%
 
79976431.751< 0.1%
 
78854847.891< 0.1%
 

SALDOTOTAL_ACT
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct46021
Distinct (%)94.6%
Missing319
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean8411400.313
Minimum-19509915.75
Maximum113877907.3
Zeros2105
Zeros (%)4.3%
Memory size382.7 KiB
2020-12-01T15:04:51.182036image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-19509915.75
5-th percentile0
Q12169046.955
median5613834.84
Q311188705.32
95-th percentile26796530.29
Maximum113877907.3
Range133387823
Interquartile range (IQR)9019658.365

Descriptive statistics

Standard deviation9615150.287
Coefficient of variation (CV)1.143109343
Kurtosis10.72306396
Mean8411400.313
Median Absolute Deviation (MAD)4041702.68
Skewness2.6270489
Sum4.093239734e+11
Variance9.245111504e+13
MonotocityNot monotonic
2020-12-01T15:04:51.364949image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
021054.3%
 
122< 0.1%
 
1604594.1717< 0.1%
 
-3410< 0.1%
 
-159< 0.1%
 
-79< 0.1%
 
-319< 0.1%
 
-439< 0.1%
 
-58< 0.1%
 
-188< 0.1%
 
Other values (46011)4645794.8%
 
(Missing)3190.7%
 
ValueCountFrequency (%) 
-19509915.751< 0.1%
 
-13755959.581< 0.1%
 
-12416641.131< 0.1%
 
-10200329.151< 0.1%
 
-8913752.491< 0.1%
 
ValueCountFrequency (%) 
113877907.31< 0.1%
 
106794779.31< 0.1%
 
103620867.81< 0.1%
 
102902115.21< 0.1%
 
100504771.61< 0.1%
 

FECHAMOVIMIENTO
Categorical

HIGH CARDINALITY

Distinct517
Distinct (%)1.1%
Missing74
Missing (%)0.2%
Memory size382.7 KiB
2019-11-13
14480 
2020-07-07
9633 
2020-09-08
 
1863
2020-09-22
 
1538
2020-06-24
 
1460
Other values (512)
19934 
ValueCountFrequency (%) 
2019-11-131448029.6%
 
2020-07-07963319.7%
 
2020-09-0818633.8%
 
2020-09-2215383.1%
 
2020-06-2414603.0%
 
2020-02-2611112.3%
 
2020-08-1910472.1%
 
2020-11-108941.8%
 
2020-07-036591.3%
 
2019-04-043110.6%
 
Other values (507)1591232.5%
 
2020-12-01T15:04:51.569844image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique89 ?
Unique (%)0.2%
2020-12-01T15:04:51.746174image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.989424687
Min length3

CALIFICACIONACTUAL
Categorical

MISSING

Distinct7
Distinct (%)< 0.1%
Missing2592
Missing (%)5.3%
Memory size382.7 KiB
K
36696 
E
9499 
DD
 
78
D
 
74
K
 
41
Other values (2)
 
2
ValueCountFrequency (%) 
K3669674.9%
 
E949919.4%
 
DD780.2%
 
D740.2%
 
K 410.1%
 
BB1< 0.1%
 
AA1< 0.1%
 
(Missing)25925.3%
 
2020-12-01T15:04:51.904202image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-12-01T15:04:52.014156image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:04:52.239227image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length1
Mean length1.110816218
Min length1

VCTO_CUOTA1
Categorical

HIGH CARDINALITY
MISSING

Distinct954
Distinct (%)2.0%
Missing1034
Missing (%)2.1%
Memory size382.7 KiB
2019-01-05
 
2680
2018-12-05
 
2420
2015-12-17
 
1784
2017-07-05
 
1657
2011-07-02
 
1352
Other values (949)
38055 
ValueCountFrequency (%) 
2019-01-0526805.5%
 
2018-12-0524204.9%
 
2015-12-1717843.6%
 
2017-07-0516573.4%
 
2011-07-0213522.8%
 
2014-08-1712662.6%
 
2018-02-0512112.5%
 
2017-01-2011722.4%
 
2016-12-2011412.3%
 
2013-02-0511302.3%
 
Other values (944)3213565.6%
 
2020-12-01T15:04:52.424237image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique421 ?
Unique (%)0.9%
2020-12-01T15:04:52.595143image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.852231432
Min length3

FECHA_VCTO
Categorical

HIGH CARDINALITY
MISSING

Distinct2047
Distinct (%)4.3%
Missing990
Missing (%)2.0%
Memory size382.7 KiB
2024-12-05
 
912
2018-06-05
 
613
2020-12-05
 
487
2022-12-05
 
471
2018-12-20
 
423
Other values (2042)
45086 
ValueCountFrequency (%) 
2024-12-059121.9%
 
2018-06-056131.3%
 
2020-12-054871.0%
 
2022-12-054711.0%
 
2018-12-204230.9%
 
2021-12-053960.8%
 
2019-06-053810.8%
 
2020-10-053720.8%
 
2020-07-173680.8%
 
2020-12-203490.7%
 
Other values (2037)4322088.2%
 
(Missing)9902.0%
 
2020-12-01T15:04:52.775208image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique739 ?
Unique (%)1.5%
2020-12-01T15:04:52.941254image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length9.858519456
Min length3

FECHAULTPAGO
Categorical

HIGH CARDINALITY
MISSING

Distinct1130
Distinct (%)5.6%
Missing28842
Missing (%)58.9%
Memory size382.7 KiB
2018-10-30
 
475
2019-02-28
 
350
2019-09-30
 
192
2020-09-22
 
189
2020-08-31
 
163
Other values (1125)
18771 
ValueCountFrequency (%) 
2018-10-304751.0%
 
2019-02-283500.7%
 
2019-09-301920.4%
 
2020-09-221890.4%
 
2020-08-311630.3%
 
2019-08-301600.3%
 
2020-09-211450.3%
 
2020-07-311440.3%
 
2020-09-301240.3%
 
2020-02-281180.2%
 
Other values (1120)1808036.9%
 
(Missing)2884258.9%
 
2020-12-01T15:04:53.114141image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique383 ?
Unique (%)1.9%
2020-12-01T15:04:53.277348image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length3
Mean length5.878200155
Min length3

SALDOINICIAAMORT
Real number (ℝ≥0)

Distinct47896
Distinct (%)98.5%
Missing333
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean9538704.363
Minimum0
Maximum94723156
Zeros36
Zeros (%)0.1%
Memory size382.7 KiB
2020-12-01T15:04:53.444252image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile954666.42
Q13414070.93
median6896904.01
Q312806253
95-th percentile26243843.99
Maximum94723156
Range94723156
Interquartile range (IQR)9392182.07

Descriptive statistics

Standard deviation9049199.759
Coefficient of variation (CV)0.9486822754
Kurtosis9.015672172
Mean9538704.363
Median Absolute Deviation (MAD)4235939.48
Skewness2.373503809
Sum4.640484286e+11
Variance8.188801628e+13
MonotocityNot monotonic
2020-12-01T15:04:53.607160image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0360.1%
 
1631753.3522< 0.1%
 
314883.1820< 0.1%
 
173225018< 0.1%
 
1710663.514< 0.1%
 
316713.098< 0.1%
 
2042970.978< 0.1%
 
1119038.587< 0.1%
 
1667732.37< 0.1%
 
1247809.597< 0.1%
 
Other values (47886)4850299.0%
 
(Missing)3330.7%
 
ValueCountFrequency (%) 
0360.1%
 
1038.171< 0.1%
 
1179.081< 0.1%
 
2318.51< 0.1%
 
36581< 0.1%
 
ValueCountFrequency (%) 
947231561< 0.1%
 
93503758.891< 0.1%
 
88872006.581< 0.1%
 
87144402.491< 0.1%
 
865737971< 0.1%
 

DEPTORESIDENCIA
Categorical

Distinct36
Distinct (%)0.1%
Missing354
Missing (%)0.7%
Memory size382.7 KiB
DISTRITO CAPITAL
8651 
ATLANTICO
7025 
BOLIVAR
6616 
VALLE DEL CAUCA
3419 
ANTIOQUIA
2612 
Other values (31)
20305 
ValueCountFrequency (%) 
DISTRITO CAPITAL865117.7%
 
ATLANTICO702514.3%
 
BOLIVAR661613.5%
 
VALLE DEL CAUCA34197.0%
 
ANTIOQUIA26125.3%
 
SUCRE22914.7%
 
SANTANDER21834.5%
 
CORDOBA20904.3%
 
CUNDINAMARCA17683.6%
 
MAGDALENA11192.3%
 
Other values (26)1085422.2%
 
2020-12-01T15:04:53.786175image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)< 0.1%
2020-12-01T15:04:53.945239image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length9
Mean length9.852292679
Min length3

MUNICRESIDENCIA
Categorical

HIGH CARDINALITY

Distinct824
Distinct (%)1.7%
Missing357
Missing (%)0.7%
Memory size382.7 KiB
BOGOTA D.C.
8468 
CARTAGENA
5766 
BARRANQUILLA
5070 
CALI
 
2357
MEDELLIN
 
1436
Other values (819)
25528 
ValueCountFrequency (%) 
BOGOTA D.C.846817.3%
 
CARTAGENA576611.8%
 
BARRANQUILLA507010.4%
 
CALI23574.8%
 
MEDELLIN14362.9%
 
SINCELEJO13632.8%
 
SOLEDAD11422.3%
 
BUCARAMANGA9882.0%
 
MONTERIA7291.5%
 
CUCUTA6651.4%
 
Other values (814)2064142.1%
 
2020-12-01T15:04:54.139127image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique163 ?
Unique (%)0.3%
2020-12-01T15:04:54.315174image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length25
Median length9
Mean length9.046853946
Min length1

CODSNIES_INST
Real number (ℝ≥0)

ZEROS

Distinct306
Distinct (%)0.6%
Missing320
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean2532.688422
Minimum0
Maximum9907
Zeros828
Zeros (%)1.7%
Memory size382.7 KiB
2020-12-01T15:04:54.465223image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1114.05
Q11729
median1832
Q32832
95-th percentile4813
Maximum9907
Range9907
Interquartile range (IQR)1103

Descriptive statistics

Standard deviation1518.676917
Coefficient of variation (CV)0.5996303784
Kurtosis8.413529948
Mean2532.688422
Median Absolute Deviation (MAD)715
Skewness2.482437179
Sum123245684
Variance2306379.578
MonotocityNot monotonic
2020-12-01T15:04:54.638111image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
371025025.1%
 
183216993.5%
 
210213602.8%
 
280512212.5%
 
180411752.4%
 
282311482.3%
 
283611002.2%
 
48139932.0%
 
18059501.9%
 
18189301.9%
 
Other values (296)3558472.6%
 
ValueCountFrequency (%) 
08281.7%
 
23290.7%
 
11011490.3%
 
1102760.2%
 
1103470.1%
 
ValueCountFrequency (%) 
990722< 0.1%
 
99069< 0.1%
 
990515< 0.1%
 
99042< 0.1%
 
99031< 0.1%
 

IES
Categorical

HIGH CARDINALITY
MISSING

Distinct297
Distinct (%)0.6%
Missing1136
Missing (%)2.3%
Memory size382.7 KiB
FUNDACION TECNOLOGICA ANTONIO DE AREVALO
 
2500
UNIVERSIDAD TECNOLOGICA DE BOLIVAR
 
1699
UNIVERSIDAD COOPERATIVA DE COLOMBIA
 
1598
UNIVERSIDAD NACIONAL ABIERTA Y A DISTANCIA UNAD
 
1360
UNIVERSIDAD SIMON BOLIVAR
 
1221
Other values (292)
39468 
ValueCountFrequency (%) 
FUNDACION TECNOLOGICA ANTONIO DE AREVALO25005.1%
 
UNIVERSIDAD TECNOLOGICA DE BOLIVAR16993.5%
 
UNIVERSIDAD COOPERATIVA DE COLOMBIA15983.3%
 
UNIVERSIDAD NACIONAL ABIERTA Y A DISTANCIA UNAD13602.8%
 
UNIVERSIDAD SIMON BOLIVAR12212.5%
 
UNIVERSIDAD LIBRE11822.4%
 
PA FIDUPREVISORAS A UNIVERSIDAD AUTONOMA DEL CARIBE11752.4%
 
CORPORACION UNIVERSITARIA DEL CARIBE11482.3%
 
CORPORACION UNIVERSITARIA EMPRESARIAL DE SALAMANCA11002.2%
 
CORPORACION UNIFICADA NACIONAL DE EDUCACION SUPERI9932.0%
 
Other values (287)3387069.1%
 
(Missing)11362.3%
 
2020-12-01T15:04:54.835151image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique27 ?
Unique (%)0.1%
2020-12-01T15:04:55.037247image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length80
Median length35
Mean length34.69554122
Min length3

NOMBREPROGRAMA
Categorical

HIGH CARDINALITY
MISSING

Distinct2279
Distinct (%)4.8%
Missing1148
Missing (%)2.3%
Memory size382.7 KiB
DERECHO
4326 
CONTADURIA PUBLICA
 
2300
PSICOLOGIA
 
2299
ADMINISTRACION DE EMPRESAS
 
1897
MEDICINA
 
1821
Other values (2274)
35191 
ValueCountFrequency (%) 
DERECHO43268.8%
 
CONTADURIA PUBLICA23004.7%
 
PSICOLOGIA22994.7%
 
ADMINISTRACION DE EMPRESAS18973.9%
 
MEDICINA18213.7%
 
INGENIERIA INDUSTRIAL16663.4%
 
INGENIERIA DE SISTEMAS11912.4%
 
TECNOLOGIA EN SALUD OCUPACIONAL11102.3%
 
INGENIERIA CIVIL10462.1%
 
ENFERMERIA9311.9%
 
Other values (2269)2924759.7%
 
(Missing)11482.3%
 
2020-12-01T15:04:55.239133image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique898 ?
Unique (%)1.9%
2020-12-01T15:04:55.415074image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length100
Median length22
Mean length25.23867951
Min length3

NIVELDEFORMACION
Categorical

Distinct14
Distinct (%)< 0.1%
Missing335
Missing (%)0.7%
Memory size382.7 KiB
UNIVERSITARIA
34155 
TECNOLOGICA TERMINAL
10318 
TECNICA PROFESIONAL
 
2311
ESPECIALIZACION
 
826
MAESTRIA
 
642
Other values (9)
 
395
ValueCountFrequency (%) 
UNIVERSITARIA3415569.7%
 
TECNOLOGICA TERMINAL1031821.1%
 
TECNICA PROFESIONAL23114.7%
 
ESPECIALIZACION8261.7%
 
MAESTRIA6421.3%
 
EDUCACION CONTINUADA3290.7%
 
TECNOLOGICA260.1%
 
DOCTORADO22< 0.1%
 
ESPECIALIZACION UNIVERSITARIA5< 0.1%
 
ESPECIALIZACION TECNOLOGICA4< 0.1%
 
Other values (4)9< 0.1%
 
(Missing)3350.7%
 
2020-12-01T15:04:55.595194image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T15:04:55.764131image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length33
Median length13
Mean length14.70660651
Min length3

LINEA
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing319
Missing (%)0.7%
Memory size382.7 KiB
ACCES
33891 
LINEAS TRADICIONALES
14772 
ValueCountFrequency (%) 
ACCES3389169.2%
 
LINEAS TRADICIONALES1477230.2%
 
(Missing)3190.7%
 
2020-12-01T15:04:55.917157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T15:04:56.019235image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:04:56.141134image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length20
Median length5
Mean length9.510677392
Min length3

TIPOCARTERA
Categorical

Distinct2
Distinct (%)< 0.1%
Missing319
Missing (%)0.7%
Memory size382.7 KiB
AMORTIZACION
48662 
ESTUDIOS
 
1
ValueCountFrequency (%) 
AMORTIZACION4866299.3%
 
ESTUDIOS1< 0.1%
 
(Missing)3190.7%
 
2020-12-01T15:04:56.305039image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T15:04:56.396175image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:04:56.502197image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length12
Mean length11.94130497
Min length3

ESTADOACTUAL
Categorical

MISSING

Distinct21
Distinct (%)< 0.1%
Missing2909
Missing (%)5.9%
Memory size382.7 KiB
COBRO PREJURIDICO - INGRESO
29943 
COBRO PREJURIDICO - DEVOLUCION
5292 
COBRO PREJURIDICO CARTERA K - INGRESO
3766 
COBRO ADMINISTRATIVO DEVOLUCION
 
2465
COBRO ADMINISTRATIVO INGRESO
 
2412
Other values (16)
 
2195
ValueCountFrequency (%) 
COBRO PREJURIDICO - INGRESO2994361.1%
 
COBRO PREJURIDICO - DEVOLUCION529210.8%
 
COBRO PREJURIDICO CARTERA K - INGRESO37667.7%
 
COBRO ADMINISTRATIVO DEVOLUCION24655.0%
 
COBRO ADMINISTRATIVO INGRESO24124.9%
 
RETENCION SALARIAL-INGRESO14262.9%
 
COBRO ADMINISTRATIVO CARTERA K -DEVOLUCION2150.4%
 
COBRO ADMINISTRATIVO CARTERA K - INGRESO2110.4%
 
RETENCION SALARIAL-DEVOLUCION1210.2%
 
COBRO PREJURIDICO CARTERA K - DEVOLUCION1080.2%
 
Other values (11)1140.2%
 
(Missing)29095.9%
 
2020-12-01T15:04:56.656140image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2020-12-01T15:04:56.830157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length46
Median length27
Mean length27.02080356
Min length3

SALDOCAPITALACIERRE
Real number (ℝ)

HIGH CORRELATION

Distinct48004
Distinct (%)98.7%
Missing365
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean7029252.595
Minimum-2498131.23
Maximum94723156
Zeros175
Zeros (%)0.4%
Memory size382.7 KiB
2020-12-01T15:04:56.992038image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2498131.23
5-th percentile364692.828
Q12037374.15
median4635403.81
Q39149828.36
95-th percentile21775178.55
Maximum94723156
Range97221287.23
Interquartile range (IQR)7112454.21

Descriptive statistics

Standard deviation7814236.6
Coefficient of variation (CV)1.111673893
Kurtosis12.49686312
Mean7029252.595
Median Absolute Deviation (MAD)3092016.13
Skewness2.811419267
Sum3.417411734e+11
Variance6.106229365e+13
MonotocityNot monotonic
2020-12-01T15:04:57.151221image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
01750.4%
 
94104023< 0.1%
 
946508.758< 0.1%
 
28526797< 0.1%
 
2173494.57< 0.1%
 
2696480.017< 0.1%
 
2633333.177< 0.1%
 
1247809.597< 0.1%
 
9395527< 0.1%
 
2233447.987< 0.1%
 
Other values (47994)4836298.7%
 
(Missing)3650.7%
 
ValueCountFrequency (%) 
-2498131.231< 0.1%
 
-4677891< 0.1%
 
-3836811< 0.1%
 
-3166791< 0.1%
 
-233333.931< 0.1%
 
ValueCountFrequency (%) 
947231561< 0.1%
 
93503758.891< 0.1%
 
88330116.581< 0.1%
 
878828381< 0.1%
 
86362867.721< 0.1%
 

CAPITALICETEX_ACT
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct44386
Distinct (%)91.2%
Missing319
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean6734558.451
Minimum-2498131.23
Maximum94723155.76
Zeros3863
Zeros (%)7.9%
Memory size382.7 KiB
2020-12-01T15:04:57.329161image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2498131.23
5-th percentile0
Q11642084.765
median4384667
Q38933521.23
95-th percentile21523460.92
Maximum94723155.76
Range97221286.99
Interquartile range (IQR)7291436.465

Descriptive statistics

Standard deviation7869618.489
Coefficient of variation (CV)1.168542607
Kurtosis12.21843224
Mean6734558.451
Median Absolute Deviation (MAD)3257906.2
Skewness2.767087601
Sum3.277238179e+11
Variance6.193089516e+13
MonotocityNot monotonic
2020-12-01T15:04:57.487297image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
038637.9%
 
94104022< 0.1%
 
946508.758< 0.1%
 
2696480.017< 0.1%
 
28526797< 0.1%
 
9395527< 0.1%
 
2173494.57< 0.1%
 
2633333.177< 0.1%
 
1247809.597< 0.1%
 
2233447.987< 0.1%
 
Other values (44376)4472191.3%
 
(Missing)3190.7%
 
ValueCountFrequency (%) 
-2498131.231< 0.1%
 
-2174006.961< 0.1%
 
-681144.31< 0.1%
 
-5970701< 0.1%
 
-590530.891< 0.1%
 
ValueCountFrequency (%) 
94723155.761< 0.1%
 
93503758.891< 0.1%
 
88330116.581< 0.1%
 
87882838.41< 0.1%
 
86362867.721< 0.1%
 

SUBLINEA
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct74
Distinct (%)0.2%
Missing319
Missing (%)0.7%
Memory size382.7 KiB
ACCES
22816 
ALIANZA
8001 
PREGRADO MP
5112 
CERES
2793 
TU ELIGES 25%
2539 
Other values (69)
7402 
ValueCountFrequency (%) 
ACCES2281646.6%
 
ALIANZA800116.3%
 
PREGRADO MP511210.4%
 
CERES27935.7%
 
TU ELIGES 25%25395.2%
 
PREGRADO LARGO PLAZO9381.9%
 
POSGRADO PAIS CON DEUDOR5811.2%
 
PREGRADO MP 50-505551.1%
 
TU ELIGES 50%4681.0%
 
POSGRADO PAIS SIN DEUDOR4500.9%
 
Other values (64)44109.0%
 
2020-12-01T15:04:57.675190image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique8 ?
Unique (%)< 0.1%
2020-12-01T15:04:57.844233image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length49
Median length5
Mean length8.577518272
Min length3

ESTRATO
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing3002
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean1.845867769
Minimum0
Maximum6
Zeros428
Zeros (%)0.9%
Memory size382.7 KiB
2020-12-01T15:04:57.969148image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q32
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8805006701
Coefficient of variation (CV)0.4770117801
Kurtosis1.378626055
Mean1.845867769
Median Absolute Deviation (MAD)1
Skewness0.9315836994
Sum84873
Variance0.7752814301
MonotocityNot monotonic
2020-12-01T15:04:58.082983image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
21857137.9%
 
11771836.2%
 
3761715.6%
 
411772.4%
 
04280.9%
 
53600.7%
 
61090.2%
 
(Missing)30026.1%
 
ValueCountFrequency (%) 
04280.9%
 
11771836.2%
 
21857137.9%
 
3761715.6%
 
411772.4%
 
ValueCountFrequency (%) 
61090.2%
 
53600.7%
 
411772.4%
 
3761715.6%
 
21857137.9%
 

SEXO
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing3123
Missing (%)6.4%
Memory size382.7 KiB
F
24180 
M
21679 
ValueCountFrequency (%) 
F2418049.4%
 
M2167944.3%
 
(Missing)31236.4%
 
2020-12-01T15:04:58.234164image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T15:04:58.322246image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:04:58.435227image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.12751623
Min length1

ESTADOCIVIL
Categorical

MISSING

Distinct12
Distinct (%)< 0.1%
Missing2964
Missing (%)6.1%
Memory size382.7 KiB
SOLTERO(A)
37885 
CASADO(A)
4000 
OTRO
 
2350
1
 
803
UNIËN LIBRE
 
502
Other values (7)
 
478
ValueCountFrequency (%) 
SOLTERO(A)3788577.3%
 
CASADO(A)40008.2%
 
OTRO23504.8%
 
18031.6%
 
UNIËN LIBRE5021.0%
 
DIVORCIADO(A) / SEPARADO(A)2710.6%
 
2900.2%
 
UNIÓN LIBRE470.1%
 
3440.1%
 
VIUDO(A)12< 0.1%
 
Other values (2)14< 0.1%
 
(Missing)29646.1%
 
2020-12-01T15:04:58.597206image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T15:04:58.762177image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length27
Median length10
Mean length9.136927851
Min length1

TIPONOVEDAD
Categorical

Distinct3
Distinct (%)< 0.1%
Missing9
Missing (%)< 0.1%
Memory size382.7 KiB
N
37719 
E
11253 
M
 
1
ValueCountFrequency (%) 
N3771977.0%
 
E1125323.0%
 
M1< 0.1%
 
(Missing)9< 0.1%
 
2020-12-01T15:04:58.927194image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T15:04:59.040243image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:04:59.179204image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.000367482
Min length1

Rangodiasmora
Categorical

MISSING

Distinct9
Distinct (%)< 0.1%
Missing12305
Missing (%)25.1%
Memory size382.7 KiB
(10) > 360
30331 
(08) 181 - 270
 
1927
(09) 271 - 360
 
1341
(02) 1 - 30
 
916
(03) 31 - 60
 
719
Other values (4)
 
1443
ValueCountFrequency (%) 
(10) > 3603033161.9%
 
(08) 181 - 27019273.9%
 
(09) 271 - 36013412.7%
 
(02) 1 - 309161.9%
 
(03) 31 - 607191.5%
 
(04) 61 - 905681.2%
 
(06) 121 - 1503370.7%
 
(05) 91 - 1203280.7%
 
(07) 151 - 1802100.4%
 
(Missing)1230525.1%
 
2020-12-01T15:04:59.344326image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T15:04:59.462259image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:04:59.729337image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length10
Mean length8.644379568
Min length3

CONCEPTO
Categorical

MISSING

Distinct5
Distinct (%)< 0.1%
Missing14625
Missing (%)29.9%
Memory size382.7 KiB
MILLENNIALS
30900 
GENERACIÓN X
 
2979
BABY BOOMERS
 
285
GENERACIÓN Z
 
192
GENERACIÓN SILENCIOSA
 
1
ValueCountFrequency (%) 
MILLENNIALS3090063.1%
 
GENERACIÓN X29796.1%
 
BABY BOOMERS2850.6%
 
GENERACIÓN Z1920.4%
 
GENERACIÓN SILENCIOSA1< 0.1%
 
(Missing)1462529.9%
 
2020-12-01T15:04:59.884249image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T15:05:00.000182image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:05:00.764226image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length21
Median length11
Mean length8.682128129
Min length3

FECHA_ACUERDO
Categorical

HIGH CARDINALITY
MISSING

Distinct1423
Distinct (%)4.2%
Missing15306
Missing (%)31.2%
Memory size382.7 KiB
2017-06-30
 
195
2019-09-10
 
154
2016-07-12
 
154
2017-09-05
 
146
2019-08-05
 
142
Other values (1418)
32885 
ValueCountFrequency (%) 
2017-06-301950.4%
 
2019-09-101540.3%
 
2016-07-121540.3%
 
2017-09-051460.3%
 
2019-08-051420.3%
 
2016-09-121380.3%
 
2018-08-101370.3%
 
2019-08-101360.3%
 
2018-09-101330.3%
 
2019-07-051320.3%
 
Other values (1413)3220965.8%
 
(Missing)1530631.2%
 
2020-12-01T15:05:00.957231image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique85 ?
Unique (%)0.3%
2020-12-01T15:05:01.139339image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length7.812625046
Min length3

ESTADO_ACUERDO
Categorical

MISSING

Distinct6
Distinct (%)< 0.1%
Missing15306
Missing (%)31.2%
Memory size382.7 KiB
INCUMPLIDO
14426 
CUMPLIDO
14318 
ANULADO
4683 
APROBADO
 
229
APROBADO EXCEPC
 
19
ValueCountFrequency (%) 
INCUMPLIDO1442629.5%
 
CUMPLIDO1431829.2%
 
ANULADO46839.6%
 
APROBADO2290.5%
 
APROBADO EXCEPC19< 0.1%
 
O1< 0.1%
 
(Missing)1530631.2%
 
2020-12-01T15:05:01.303240image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T15:05:01.416254image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:05:01.618335image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length8
Mean length6.933587849
Min length1

TIPO_ACUERDO
Categorical

MISSING

Distinct7
Distinct (%)< 0.1%
Missing15306
Missing (%)31.2%
Memory size382.7 KiB
REFINANCIACION
13940 
ABONO
6803 
NORMALIZACION
6233 
EXTINCION
4040 
ABONOPV
2486 
Other values (2)
 
174
ValueCountFrequency (%) 
REFINANCIACION1394028.5%
 
ABONO680313.9%
 
NORMALIZACION623312.7%
 
EXTINCION40408.2%
 
ABONOPV24865.1%
 
ABONOPT1730.4%
 
AMORTIZACION1< 0.1%
 
(Missing)1530631.2%
 
2020-12-01T15:05:01.781256image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-12-01T15:05:01.900187image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:05:02.162935image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length7
Mean length8.393021926
Min length3

CUOTAS_PAGADAS_ACUERDO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct34
Distinct (%)0.1%
Missing23473
Missing (%)47.9%
Infinite0
Infinite (%)0.0%
Mean0.7095142891
Minimum0
Maximum36
Zeros14348
Zeros (%)29.3%
Memory size382.7 KiB
2020-12-01T15:05:02.309732image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum36
Range36
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.183946274
Coefficient of variation (CV)3.078086387
Kurtosis118.1374431
Mean0.7095142891
Median Absolute Deviation (MAD)0
Skewness9.772485416
Sum18099
Variance4.76962133
MonotocityNot monotonic
2020-12-01T15:05:02.466921image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%) 
01434829.3%
 
11012720.7%
 
22550.5%
 
31600.3%
 
41120.2%
 
6760.2%
 
5680.1%
 
7470.1%
 
24450.1%
 
9350.1%
 
Other values (24)2360.5%
 
(Missing)2347347.9%
 
ValueCountFrequency (%) 
01434829.3%
 
11012720.7%
 
22550.5%
 
31600.3%
 
41120.2%
 
ValueCountFrequency (%) 
3620< 0.1%
 
351< 0.1%
 
345< 0.1%
 
332< 0.1%
 
322< 0.1%
 

CUOTAS_MORA_ACUERDO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct43
Distinct (%)0.2%
Missing23473
Missing (%)47.9%
Infinite0
Infinite (%)0.0%
Mean1.556940688
Minimum0
Maximum47
Zeros12558
Zeros (%)25.6%
Memory size382.7 KiB
2020-12-01T15:05:02.637168image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile9
Maximum47
Range47
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.456137809
Coefficient of variation (CV)2.862111476
Kurtosis25.81324986
Mean1.556940688
Median Absolute Deviation (MAD)1
Skewness4.848328713
Sum39716
Variance19.85716417
MonotocityNot monotonic
2020-12-01T15:05:02.795198image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%) 
01255825.6%
 
11042121.3%
 
24360.9%
 
32300.5%
 
121780.4%
 
241650.3%
 
61650.3%
 
181380.3%
 
51360.3%
 
41230.3%
 
Other values (33)9592.0%
 
(Missing)2347347.9%
 
ValueCountFrequency (%) 
01255825.6%
 
11042121.3%
 
24360.9%
 
32300.5%
 
41230.3%
 
ValueCountFrequency (%) 
471< 0.1%
 
422< 0.1%
 
413< 0.1%
 
401< 0.1%
 
392< 0.1%
 

CUOTAS_FUTURAS_ACUERDO
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct60
Distinct (%)0.2%
Missing23473
Missing (%)47.9%
Infinite0
Infinite (%)0.0%
Mean0.2872319573
Minimum0
Maximum173
Zeros25087
Zeros (%)51.2%
Memory size382.7 KiB
2020-12-01T15:05:02.961139image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum173
Range173
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.572231656
Coefficient of variation (CV)15.9182554
Kurtosis527.0918458
Mean0.2872319573
Median Absolute Deviation (MAD)0
Skewness21.17064286
Sum7327
Variance20.90530231
MonotocityNot monotonic
2020-12-01T15:05:03.111198image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
02508751.2%
 
12690.5%
 
5512< 0.1%
 
3611< 0.1%
 
211< 0.1%
 
39< 0.1%
 
357< 0.1%
 
47< 0.1%
 
545< 0.1%
 
424< 0.1%
 
Other values (50)870.2%
 
(Missing)2347347.9%
 
ValueCountFrequency (%) 
02508751.2%
 
12690.5%
 
211< 0.1%
 
39< 0.1%
 
47< 0.1%
 
ValueCountFrequency (%) 
1731< 0.1%
 
1551< 0.1%
 
1451< 0.1%
 
1381< 0.1%
 
1352< 0.1%
 

fecha Venc Cuota Vigente
Categorical

HIGH CARDINALITY
MISSING

Distinct103
Distinct (%)0.7%
Missing33410
Missing (%)68.2%
Memory size382.7 KiB
2020-02-20
5441 
2020-05-02
4913 
2020-02-17
2329 
2020-10-02
1394 
2020-03-02
 
234
Other values (98)
1261 
ValueCountFrequency (%) 
2020-02-20544111.1%
 
2020-05-02491310.0%
 
2020-02-1723294.8%
 
2020-10-0213942.8%
 
2020-03-022340.5%
 
2020-01-282270.5%
 
2020-01-301650.3%
 
2020-01-31890.2%
 
2020-05-03790.2%
 
2020-03-20660.1%
 
Other values (93)6351.3%
 
(Missing)3341068.2%
 
2020-12-01T15:05:03.303214image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique47 ?
Unique (%)0.3%
2020-12-01T15:05:03.493092image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length3
Mean length5.225388918
Min length3

Valor Cuota Vigente
Categorical

HIGH CARDINALITY
MISSING

Distinct6843
Distinct (%)20.3%
Missing15306
Missing (%)31.2%
Memory size382.7 KiB
0
26746 
335106
 
3
599851
 
3
116905
 
3
52930
 
3
Other values (6838)
6918 
ValueCountFrequency (%) 
02674654.6%
 
3351063< 0.1%
 
5998513< 0.1%
 
1169053< 0.1%
 
529303< 0.1%
 
160354,163< 0.1%
 
565372< 0.1%
 
1047432< 0.1%
 
530312< 0.1%
 
1389212< 0.1%
 
Other values (6833)690714.1%
 
(Missing)1530631.2%
 
2020-12-01T15:05:03.695185image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6759 ?
Unique (%)20.1%
2020-12-01T15:05:03.883134image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length1
Mean length2.306704504
Min length1

No. ACUERDOS DE PAGO
Real number (ℝ≥0)

MISSING

Distinct32
Distinct (%)0.1%
Missing15306
Missing (%)31.2%
Infinite0
Infinite (%)0.0%
Mean3.434047987
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Memory size382.7 KiB
2020-12-01T15:05:04.066218image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q35
95-th percentile9
Maximum46
Range45
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.860770791
Coefficient of variation (CV)0.8330608082
Kurtosis9.723459991
Mean3.434047987
Median Absolute Deviation (MAD)2
Skewness2.299368377
Sum115645
Variance8.18400952
MonotocityNot monotonic
2020-12-01T15:05:04.221146image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%) 
1946419.3%
 
2685214.0%
 
3513210.5%
 
437117.6%
 
526625.4%
 
618353.7%
 
712212.5%
 
88651.8%
 
95781.2%
 
103770.8%
 
Other values (22)9792.0%
 
(Missing)1530631.2%
 
ValueCountFrequency (%) 
1946419.3%
 
2685214.0%
 
3513210.5%
 
437117.6%
 
526625.4%
 
ValueCountFrequency (%) 
461< 0.1%
 
391< 0.1%
 
312< 0.1%
 
301< 0.1%
 
293< 0.1%
 

RazonSocial
Categorical

HIGH CARDINALITY
MISSING

Distinct19241
Distinct (%)61.9%
Missing17908
Missing (%)36.6%
Memory size382.7 KiB
CORPORACION UNIVERSITARIA DEL CARIBE, CECAR.
 
198
REGISTRADURIA NACIONAL DEL ESTADO CIVIL
 
186
COMFENALCO
 
142
UNIVERSIDAD COOPERATIVA DE COLOMBIA
 
140
UNIVERSIDAD SIMON BOLIVAR
 
135
Other values (19236)
30273 
ValueCountFrequency (%) 
CORPORACION UNIVERSITARIA DEL CARIBE, CECAR.1980.4%
 
REGISTRADURIA NACIONAL DEL ESTADO CIVIL1860.4%
 
COMFENALCO1420.3%
 
UNIVERSIDAD COOPERATIVA DE COLOMBIA1400.3%
 
UNIVERSIDAD SIMON BOLIVAR1350.3%
 
S E N A1310.3%
 
ACTIVOS SAS1150.2%
 
TELEPERFORMANCE COLOMBIA S A S1070.2%
 
ALMACENES EXITO S A1060.2%
 
CAJA COLOMBIANA DE SUBSIDIO FAMILIAR COLSUBSI1000.2%
 
Other values (19231)2971460.7%
 
(Missing)1790836.6%
 
2020-12-01T15:05:04.446249image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique16550 ?
Unique (%)53.3%
2020-12-01T15:05:04.660320image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length180
Median length18
Mean length18.47701196
Min length3

UltimoPeriodoCotizado
Categorical

HIGH CARDINALITY
MISSING

Distinct174
Distinct (%)0.5%
Missing14172
Missing (%)28.9%
Memory size382.7 KiB
2020-10
8670 
2020-09
4482 
1900-01
3736 
2020-08
 
1487
2019-12
 
747
Other values (169)
15688 
ValueCountFrequency (%) 
2020-10867017.7%
 
2020-0944829.2%
 
1900-0137367.6%
 
2020-0814873.0%
 
2019-127471.5%
 
2019-116701.4%
 
2020-076331.3%
 
2020-016321.3%
 
2020-046301.3%
 
2020-065411.1%
 
Other values (164)1258225.7%
 
(Missing)1417228.9%
 
2020-12-01T15:05:04.904195image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique8 ?
Unique (%)< 0.1%
2020-12-01T15:05:05.088183image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length7
Mean length5.842676902
Min length3

FechaFosyga
Categorical

MISSING

Distinct1
Distinct (%)< 0.1%
Missing14172
Missing (%)28.9%
Memory size382.7 KiB
2020-10-01
34810 
ValueCountFrequency (%) 
2020-10-013481071.1%
 
(Missing)1417228.9%
 
2020-12-01T15:05:05.269094image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-01T15:05:05.362963image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2020-12-01T15:05:05.467889image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length7.974684578
Min length3

Hora_ContactoEfectivo
Real number (ℝ≥0)

MISSING

Distinct14
Distinct (%)< 0.1%
Missing20802
Missing (%)42.5%
Infinite0
Infinite (%)0.0%
Mean11.10809084
Minimum7
Maximum20
Zeros0
Zeros (%)0.0%
Memory size382.7 KiB
2020-12-01T15:05:05.633841image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile8
Q19
median11
Q313
95-th percentile16
Maximum20
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.80992772
Coefficient of variation (CV)0.252962256
Kurtosis-0.3780261183
Mean11.10809084
Median Absolute Deviation (MAD)2
Skewness0.6365925316
Sum313026
Variance7.895693789
MonotocityNot monotonic
2020-12-01T15:05:05.764213image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
945959.4%
 
842788.7%
 
1037487.7%
 
1132176.6%
 
1227115.5%
 
1322194.5%
 
1519133.9%
 
1418663.8%
 
713022.7%
 
1612302.5%
 
Other values (4)11012.2%
 
(Missing)2080242.5%
 
ValueCountFrequency (%) 
713022.7%
 
842788.7%
 
945959.4%
 
1037487.7%
 
1132176.6%
 
ValueCountFrequency (%) 
2021< 0.1%
 
192680.5%
 
182720.6%
 
175401.1%
 
1612302.5%
 

Llamadas_recibidas
Real number (ℝ≥0)

MISSING

Distinct38
Distinct (%)0.1%
Missing11236
Missing (%)22.9%
Infinite0
Infinite (%)0.0%
Mean4.026439888
Minimum1
Maximum48
Zeros0
Zeros (%)0.0%
Memory size382.7 KiB
2020-12-01T15:05:05.902231image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile10
Maximum48
Range47
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.179379569
Coefficient of variation (CV)0.7896254899
Kurtosis7.900779322
Mean4.026439888
Median Absolute Deviation (MAD)2
Skewness1.999249804
Sum151982
Variance10.10845444
MonotocityNot monotonic
2020-12-01T15:05:06.066181image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%) 
1810816.6%
 
2683113.9%
 
3570311.6%
 
444949.2%
 
534667.1%
 
625385.2%
 
718733.8%
 
814523.0%
 
99401.9%
 
106861.4%
 
Other values (28)16553.4%
 
(Missing)1123622.9%
 
ValueCountFrequency (%) 
1810816.6%
 
2683113.9%
 
3570311.6%
 
444949.2%
 
534667.1%
 
ValueCountFrequency (%) 
481< 0.1%
 
431< 0.1%
 
411< 0.1%
 
361< 0.1%
 
342< 0.1%
 

Llamadas_realizadas
Real number (ℝ≥0)

MISSING

Distinct99
Distinct (%)0.2%
Missing3240
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean15.02476936
Minimum1
Maximum164
Zeros0
Zeros (%)0.0%
Memory size382.7 KiB
2020-12-01T15:05:06.260212image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median12
Q321
95-th percentile38
Maximum164
Range163
Interquartile range (IQR)15

Descriptive statistics

Standard deviation11.99213699
Coefficient of variation (CV)0.7981578086
Kurtosis3.429694931
Mean15.02476936
Median Absolute Deviation (MAD)7
Skewness1.425010291
Sum687263
Variance143.8113495
MonotocityNot monotonic
2020-12-01T15:05:06.419009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
121754.4%
 
421484.4%
 
321384.4%
 
220934.3%
 
520804.2%
 
720484.2%
 
620424.2%
 
819474.0%
 
918333.7%
 
1017653.6%
 
Other values (89)2547352.0%
 
(Missing)32406.6%
 
ValueCountFrequency (%) 
121754.4%
 
220934.3%
 
321384.4%
 
421484.4%
 
520804.2%
 
ValueCountFrequency (%) 
1641< 0.1%
 
1331< 0.1%
 
1321< 0.1%
 
1181< 0.1%
 
1161< 0.1%
 

Tipificacion
Categorical

HIGH CARDINALITY
MISSING

Distinct92
Distinct (%)0.2%
Missing2524
Missing (%)5.2%
Memory size382.7 KiB
NO EFECTIVO_NO LO CONOCEN_NAN_NAN
9923 
NO CONTACTADO_NO CONTESTA_NAN_NAN
7730 
NO CONTACTADO_BUZON_NAN_NAN
5738 
NO EFECTIVO_MENSAJE CON TERCERO_NAN_NAN
3468 
EFECTIVO_COMPROMISO DE PAGO_NAN_NAN
 
1762
Other values (87)
17837 
ValueCountFrequency (%) 
NO EFECTIVO_NO LO CONOCEN_NAN_NAN992320.3%
 
NO CONTACTADO_NO CONTESTA_NAN_NAN773015.8%
 
NO CONTACTADO_BUZON_NAN_NAN573811.7%
 
NO EFECTIVO_MENSAJE CON TERCERO_NAN_NAN34687.1%
 
EFECTIVO_COMPROMISO DE PAGO_NAN_NAN17623.6%
 
OTROS_CAIDA_NAN_NAN17513.6%
 
EFECTIVO_NO REALIZA PAGO_RENUENTE_NAN17023.5%
 
EFECTIVO_NO REALIZA PAGO_INSOLVENTE_NAN16333.3%
 
EFECTIVO_CR DITO ADMINISTRATIVO_NAN_NAN11932.4%
 
EFECTIVO_PROGRAMACI N DE LLAMADA_NAN_NAN11222.3%
 
Other values (82)1043621.3%
 
(Missing)25245.2%
 
2020-12-01T15:05:06.633213image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique12 ?
Unique (%)< 0.1%
2020-12-01T15:05:06.867080image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length81
Median length33
Mean length33.85143522
Min length3

Interactions

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Correlations

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Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
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Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
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Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
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Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
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Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

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Sample

First rows

IDSOLICITUDFECHAENTRADAFECHASALIDAFECHAACTUALIZACIONFECHAMORADESDENROCUOTASMORANUMDIASMORA_ACTVALORCUOTASALDOTOTALMORA1_ACTSALDOTOTAL_ACTFECHAMOVIMIENTOCALIFICACIONACTUALVCTO_CUOTA1FECHA_VCTOFECHAULTPAGOSALDOINICIAAMORTDEPTORESIDENCIAMUNICRESIDENCIACODSNIES_INSTIESNOMBREPROGRAMANIVELDEFORMACIONLINEATIPOCARTERAESTADOACTUALSALDOCAPITALACIERRECAPITALICETEX_ACTSUBLINEAESTRATOSEXOESTADOCIVILTIPONOVEDADRangodiasmoraCONCEPTOFECHA_ACUERDOESTADO_ACUERDOTIPO_ACUERDOCUOTAS_PAGADAS_ACUERDOCUOTAS_MORA_ACUERDOCUOTAS_FUTURAS_ACUERDOfecha Venc Cuota VigenteValor Cuota VigenteNo. ACUERDOS DE PAGORazonSocialUltimoPeriodoCotizadoFechaFosygaHora_ContactoEfectivoLlamadas_recibidasLlamadas_realizadasTipificacion
02802020-11-17NaN2020-11-17NaN0.06.0218384.59231102.874248178.842020-11-17K2010-01-312022-06-102020-10-1527788677.09VALLE DEL CAUCAZARZAL1834.0UNIVERSIDAD DEL SINU Elias Bechara Zainum - UNISINMEDICINAUNIVERSITARIAACCESAMORTIZACIONCOBRO ADMINISTRATIVO DEVOLUCION4001850.624001850.62ACCES1.0FSOLTERO(A)NNaNNaN2017-09-22INCUMPLIDONORMALIZACION0.01.00.02020-10-022870943.0NaNNaNNaNNaN1.01.0NO CONTACTADO_BUZON_NAN_NAN
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211322020-11-102020-11-172020-11-17NaN0.011.0167036.95269.366514205.032020-11-17K2011-07-022024-04-052020-10-0219772924.31VALLE DEL CAUCACALI1805.0UNIVERSIDAD SANTIAGO DE CALIDERECHOUNIVERSITARIAACCESAMORTIZACIONCOBRO PREJURIDICO - INGRESO6566208.216422071.95ACCES2.0FSOLTERO(A)ENaNNaN2019-05-08INCUMPLIDOABONO0.01.00.02020-02-2008.0NaNNaNNaN7.010.030.0EFECTIVO_YA PAGO_PENDIENTE CONDONACI N_NAN
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